Evidence that dendrites actively process information in the brain

October 29, 2013

University of North Carolina at Chapel Hill researchers have discovered that dendrites do more than passively relay information from one neuron to the next — they actively process information, according to Spencer Smith, PhD, an assistant professor in the UNC School of Medicine.

Axons are where neurons conventionally generate electrical spikes, but many of the same molecules that support axonal electrical spikes (firing) are also present in dendrites.

Previous research using dissected brain tissue had demonstrated that dendrites can use those molecules to generate electrical spikes themselves, but it was unclear whether normal brain activity uses those dendritic spikes.

For example, could dendritic spikes be involved in how we see?

The evidence

A pipette (white object at top) attached to a dendrite in the brain of a mouse, allowing researchers to measure electrical activity at a dendritic spike in the mouse primary visualcortex (credit: University of North Carolina at Chapel Hill)

To find out, the researchers used a two-photon microscope system and they used patch-clamp electrophysiology to attach a microscopic glass pipette electrode, filled with a physiological solution, to a neuronal dendrite in the brain of a mouse.

As the mice viewed visual stimuli on a computer screen, the researchers saw an unusual pattern of electrical signals — bursts of spikes — in the dendrite.

Smith’s team then found that the dendritic spikes occurred selectively, depending on the visual stimulus, indicating that the dendrites in fact processed information about what the animal was seeing.

To provide visual evidence of their finding, Smith’s team filled neurons with calcium dye, which provided an optical readout of spiking.

This revealed that dendrites fired spikes while other parts of the neuron did not, meaning that the spikes were the result of local processing within the dendrites — not a electrical signal from the body of the neuron.

Schematic of the recording and imaging setup for in vivo dendritic recordings of responses to visual stimulation (left) using a patch clamp (rod) and two-photon microscope (top) (credit: Spencer L. Smith et al./Nature)

Study co-author Tiago Branco, PhD, created a biophysical, mathematical model of neurons and found that known mechanisms could support the dendritic spiking recorded electrically, further validating the interpretation of the data.

The team plans to explore what this newly discovered dendritic role may play in brain circuitry, particularly in conditions like Timothy syndrome, in which the integration of dendritic signals may go awry.

This work was supported by a Long-Term Fellowship and a Career Development Award from the Human Frontier Science Program, and a Klingenstein Fellowship to S. Smith, a Helen Lyng White Fellowship to I. Smith, a Wellcome Trust and Royal Society Fellowship, and Medical Research Council (UK) support to T. Branco, and grants from the Wellcome Trust, the European Research Council, and Gatsby Charitable Foundation to M. Häusser.

Abstract of Nature paper

Neuronal dendrites are electrically excitable: they can generate regenerative events such as dendritic spikes in response to sufficiently strong synaptic input. Although such events have been observed in many neuronal types, it is not well understood how active dendrites contribute to the tuning of neuronal output in vivo. Here we show that dendritic spikes increase the selectivity of neuronal responses to the orientation of a visual stimulus (orientation tuning). We performed direct patch-clamp recordings from the dendrites of pyramidal neurons in the primary visual cortex of lightly anaesthetized and awake mice, during sensory processing. Visual stimulation triggered regenerative local dendritic spikes that were distinct from back-propagating action potentials. These events were orientation tuned and were suppressed by either hyperpolarization of membrane potential or intracellular blockade of NMDA (N-methyl-D-aspartate) receptors. Both of these manipulations also decreased the selectivity of subthreshold orientation tuning measured at the soma, thus linking dendritic regenerative events to somatic orientation tuning. Together, our results suggest that dendritic spikes that are triggered by visual input contribute to a fundamental cortical computation: enhancing orientation selectivity in the visual cortex. Thus, dendritic excitability is an essential component of behaviourally relevant computations in neurons.

Comments (18)

Didn’t Roger Penrose predict this many years ago in one of his books. It was either in “the emperor’s new mind” or that other one. Both of them were about the uncertainty principle and more to explain consciousness in the brain. Although his point about the consciousness was not very strong, it still was very interesting. And the fact that the uncertainty principle plays an important role within the dendrites was very plausible. Hoping to hear in the next years what the role of the dendrites is. It might turn out that Penrose was completely right about everything. The man has proven to be very smart.

The hard problem of consciousness may eventually be determined by biologists and other scientists. This implies there may exist a primary entity before mental activity commences. For example, there is a continuous flow of energy throughout the universe that becomes converted into matter. And there is a continuous flow and transfer of ‘information’ within and between brain cells that becomes converted into mental activity, but the primary entity is not recognised because it is ‘silent’ and therefore only metal activity is valued. Living cells are intelligent, they ‘know’ how to function and are able to cooperate and communicate with each other, yet they are devoid of mental properties. Although matter and energy are both manifestations of the same fundamental entity, there is an entity within all living things that is relative to the biological proto-consciouness dimension. This entity causes instantaneous brain cell activity, whereas when energy is utilised for mental activity, it is relative to matter and to time because the mind is mechanistic and relies on ‘information’ that was acquired in the past. When the mind is in a meditative state, or during deep sleep, it can be said that it is part of the natural dimension of consciousness, or momentarily in the dimension of ‘nothingness’. Examples are, during deep meditation, or between one thought and another, there is a ‘silent moment’ before images, thoughts or dreams commence, yet one is not brain dead during those ‘timeless’ moments. Thoughts or memories may seem real, but in the true sense, most, like dreams, are never real. Each event the mind experiences is made up of separate time-frame images. As soon as the mind thinks it is experiencing a present moment – it’s already in the past because it takes time for the cognitive mind to function. Any form of matter, including the human body and brain and the cells within are not just matter, they contain energy. Brain cells and all other living cells are merely vehicles for this Universal Consciousness, but without energy vehicles cannot function. When conditioned thoughts end, enlightenment can transform the mind, but to rely on false knowledge and beliefs, there is nothing real to find. In a way, wisdom is the cessation of thought because the ending of preconceived concepts is the beginning of wisdom. The mind tends to forget that it is similar to a computer, if false information or belief systems exist then conclusions will be wrong. When what is known or what is owned is overvalued then the mind tends to forget that thoughts and ‘things’ and life are only temporarily real. This planet and all life on it will change or come to an end in the future, yet the future, the past and time, are mainly constructs of minds. When a secondary consciousness occurs in living things, then it seems that languages, spiritual dimensions and gods are creations of human mental activities. But, it is energy (not temporal matter) that remains the fundamental property of everything in the universe – including consciousness.

@Mitch:
If we ever reach a point of full control over the brain, one needs never feel dissatisfied again. One can shut down all undesired emotions, temporarily or permanently, and deal with whatever evolutionary leftovers in the mind or body displease them. One can re-create themselves in whatever way suits them, and perhaps ultimately not quite resemble what was once considered ‘human’ any more.

I believe long term-happiness and satisfaction might not be in the cards for us evolutionarily. It seems to make sense that an organism always desires more; to keep it motivated, competitive. With complete control over the brain though, one can feel however they wish, whenever they wish, and still lose no functionality or practicality because of it.

The whole idea really isn’t quite as insane as it might seem, truly. Just a tad unconventional, and it might take some getting used to. But we’ll get there, one step at a time. And it’ll be glorious to be free of the tyranny of biology, and free to choose what emotions we wish to experience, and when.

The more we learn, the more we discover we have left to learn. Some may use this to proclaim how much longer the singularity will take. When you are talking exponential curves however it is still reduced down to a minor bump in the road.

So it will require more modeling in simulation…and more computing power. Surely you know that such is doubling every year. There will also need to be some research on how individual neurons respond to specific stimuli. (We may even end up with a “zoo” of neuronal types by configuration.) Accuracy in genetics requires information all the way down to base pairs – differentiating individual molecules (A, C, G, T)…personally, I’m relieved that cognitive processing will be studied at something approaching this resolution, and probably with a “bigger alphabet” than four letters. It’s just more number crunching, and we can handle that.

Guys relax, this observation that dendrites have activation threshold doesn’t mean anything will be postponed. Its just a matter of understanding how these thresholds are set. As long as it’s not quantum mechanics based, everything is good.

Indeed, yet another indication that the computational ability/complexity of the brain is higher than theorized so far. And next we’ll start to have preliminary assessment of the additional computational complexity induced by neurotransmitters and other chemically regulated processing.

If I understand this correctly, Henry Markram’s job just became even more complex. To emulate a particular brain’s activity, he now has to model processes at each dendrite terminal, not just within each neuron.

It comes on top of the recent discovery that cortical columns differ widely, which closes off another short-cut.

Do these discoveries push back the likely completion of any brain emulation project by, say, a decade or so?

Looking at the human genome project, the vast (vast, vast) majority of the work got done in the last few years of the project. Most “computerized” processes seem to work that way. As such there’ll likely be an “accelerated return” in this project, and whatever years will be tacked on at the end of it will be extremely productive ones.

This merely adds to the brain’s versatility IMO, and is probably just a good thing.

snake0 wrote: “Not if the process is predictable and repetitive – then its just a matter of seeking out the model and throwing more hardware at it”

Yes, this seems true to me. And, even if a mistake is made, that doesn’t mean that a brain that gets 90% of thinking correct in far superior hardware won’t yield a number of useful insights anyway. Moreover, even if wetware has useful abilities that a synthetic computer does not, the inverse is also true: synthetics have the potential for far greater speed, more perfect memory, controlled forgetting (of things that we rationally deem as less important, in spite of what our emotions tell us), etc.

For just one example: there are people who “drink to forget” traumatic experiences. Their emotions tell them the experiences are important, but the repeated interruption of their thoughts with these memories is purely destructive (especially during working hours). So, the ability to choose what information goes where is likely to be a huge benefit, even if it weren’t accompanied with superior speed.

I think there will be billions of different kinds of brains, and that all of them will spread out and occupy interesting niches in our world and beyond. I think they will make the surrounding planets grow jungles that are pleasing to the frontier-minded on their surfaces (in all the varieties we can imagine, and many that we cannot). I don’t think that there will simply be a computronium shell, but rather that computronium will work its way into the biosphere, growing computational jungles (and other rich environments), full of rich earth (and sand) that intertwines all plants and animals –as it currently does– but with more and more general intelligence.

What I think this means (with my current very limited human capacity) is that there will be cellular-automata-based pattern-recognizing brains of all kinds. There will be exponential-recognizing (recognizing-and-predicting) modules in such brains, just as there are linear modules (as there are in most human brains) and crowd-behavior-modeling modules (as there are in some human brains). The art and science of brain-building will explode, as de Garis predicted it would. (I have no idea why he isn’t pursuing this dream of his. It makes me wonder if he’s a prisoner of the Chinese government, or if he’s in debt, or what. Whatever the situation is, the man should have a budget to work with, because he has many incredible ideas about brain-building.)

Also, all of our intelligences will model things that make our lives more interesting, such as how precisely all of our gardens grow, and what ways we can optimize them for human sensory enjoyment. I think biological design will occupy most supermodified humans’ time in the 21st century, because, as Kurzweil notes in his movie “The Singularity is Near” time will (if the sociopaths in government don’t usher in a new dark ages) become more productive in the later decades of the century.

That depends on how you look at it.
It might mean that current efforts to simulate brains, whilst worthwhile and enlightening, will not be as accurate or complete as we hoped they would be. In the long(er) term, however, even a thousandfold increase in brain complexity would only take a few additional years of work.

What we’ve got in return is a whole new topic to investigate, namely the dendritic computational capacity (and so on).

The knowledge that we might be able to influence not just the neurons, but the dendrites as well has fascinating potential.
We might be able to modify information in the dendrite before it enters the neuron, this could lead to a host of interesting discoveries, and potentially new possibilities both of monitoring what the neuron does without stimulating it directly, and to find out what the dendrite is actually processing (and what influencing said dendrite does to its associated neuron).

Longer term still: How about hooking up nanobots to the dendrites as well as (or instead of) the neurons? It just means more points of access to the brain, maybe even without having to invade the neurons themselves all the time.

All in all I think this is very optimistic. And of course, in the end, this complexity was always already there, we just weren’t aware of it. All that this did was add to our understanding.

Right on, Jon! I also see it more as good news. If our brains didn’t process the information in the manner that they do, our lives would be less colorful. This also means that the person who finally successfully models all the processes of the brain will have accomplished something all the more amazing. (It’s only bad if it becomes a diversion, or a preoccupation that prevents as-fast-as-possible brain-building.)